Direct and indirect effects of climate on richness drive the latitudinal diversity gradient in forest trees

Data accessibility statement: Full census data are available upon reasonable request from the ForestGEO data portal, http://ctfs.si.edu/datarequest/ We thank Margie Mayfield, three anonymous reviewers and Jacob Weiner for constructive comments on the manuscript. This study was financially supported by the National Key R&D Program of China (2017YFC0506100), the National Natural Science Foundation of China (31622014 and 31570426), and the Fundamental Research Funds for the Central Universities (17lgzd24) to CC. XW was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB3103). DS was supported by the Czech Science Foundation (grant no. 16-26369S). Yves Rosseel provided us valuable suggestions on using the lavaan package conducting SEM analyses. Funding and citation information for each forest plot is available in the Supplementary Information Text 1.Peer reviewedPostprin

Genetic Parameters and Genetic Progress of Growth Traits in a Landrace Pig Population

【Objective】Four genetic parameters including days to 100 kg (DAYS_100), average daily gain (ADG_100), loin muscle area (LMA_100) and average back fat thickness (BFT_100) at 100 kg body weight in a Landrace pig population were estimated, and the correlations between traits as well as genetic and phenotypic progress of the four traits were analyzed, which could provide a basis for the genetic improvement of the target population.【Method】Records of growth traits of Landrace pigs were collected in a core breeding pig farm in Guangxi from 2002 to 2020. A fixed effect analysis on the factors affecting the growth traits of Landrace pigs was conducted by R software. In addition, the genetic parameters of the four traits were estimated with DMU software and a multi-trait animal model. Furthermore, the genetic correlations and phenotypic correlations between these traits, genetic progress and phenotypic progress were evaluated.【Result】The estimated heritability for the four growth traits of Landrace pigs, including DAYS_100, ADG_100, LMA_100 and BFT_100 were 0.399, 0.391, 0.433 and 0.421, respectively, and all of them had medium to high heritability. Both genetic correlation and phenotypic correlation between DAYS_100 and ADG_100 were significantly negative, with correlation coefficient -0.997 and -0.992, respectively. In general, the phenotypic trend of DAYS_100 was rising while the phenotypic trends of ADG_100, LMA_100 and BFT_100 were declining; the genetic trends of ADG_100 and BFT_100 showed an overall upward trend while the trends of DAYS_100 and LMA_100 were generally downward.【Conclusion】The four growth traits of Landrace pigs are medium-high heritability traits, therefore, their genetic progress can be accelerated through direct selection. There is a strong correlation between DAYS_100 and ADG_100. The management of phenotypic measurement of pig farms and the selection of target traits for pig population breeding have an important impact on the performance of growth traits. In addition, the improvements in farm production management and changes in breed structure may influence genetic progress

Exploring the mechanism of artificial selection signature in Chinese indigenous pigs by leveraging multiple bioinformatics database tools

Abstract Background Chinese indigenous pigs in Yunnan exhibit considerable phenotypic diversity, but their population structure and the biological interpretation of signatures of artificial selection require further investigation. To uncover population genetic diversity, migration events, and artificial selection signatures in Chinese domestic pigs, we sampled 111 Yunnan pigs from four breeds in Yunnan which is considered to be one of the centres of livestock domestication in China, and genotyped them using Illumina Porcine SNP60K BeadChip. We then leveraged multiple bioinformatics database tools to further investigate the signatures and associated complex traits. Results Population structure and migration analyses showed that Diannanxiaoer pigs had different genetic backgrounds from other Yunnan pigs, and Gaoligongshan may undergone the migration events from Baoshan and Saba pigs. Intriguingly, we identified a possible common target of sharing artificial selection on a 265.09 kb region on chromosome 5 in Yunnan indigenous pigs, and the genes on this region were associated with cardiovascular and immune systems. We also detected several candidate genes correlated with dietary adaptation, body size (e.g., PASCIN1, GRM4, ITPR2), and reproductive performance. In addition, the breed-sharing gene MMP16 was identified to be a human-mediated gene. Multiple lines of evidence at the mammalian genome, transcriptome, and phenome levels further supported the evidence for the causality between MMP16 variants and the metabolic diseases, brain development, and cartilage tissues in Chinese pigs. Our results suggested that the suppression of MMP16 would directly lead to inactivity and insensitivity of neuronal activity and skeletal development in Chinese indigenous pigs. Conclusion In this study, the population genetic analyses and identification of artificial selection signatures of Yunnan indigenous pigs help to build an understanding of the effect of human-mediated selection mechanisms on phenotypic traits in Chinese indigenous pigs. Further studies are needed to fully characterize the process of human-mediated genes and biological mechanisms